AI Engineer – Generative AI / LLMs / RAG
Quick Summary
We are looking for an AI Engineer with hands-on experience in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems. You will design, build,
We are looking for an AI Engineer with hands-on experience in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems. You will design, build, and deploy intelligent applications such as chatbots, copilots, and AI-powered automation tools. This role combines software engineering, machine learning, and prompt/context engineering to deliver scalable, production-ready AI systems.
Responsibilities
~1 min read- →
Design and implement AI-powered applications using LLMs (OpenAI, Anthropic, open-source models, etc.)
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Build and optimize RAG pipelines (vector databases, embeddings, retrieval strategies)
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Develop chatbots and conversational AI systems with strong context management
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Implement prompt engineering and context engineering strategies for reliable outputs
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Integrate LLMs into backend systems via APIs and microservices
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Work with vector databases (Pinecone, Weaviate, FAISS, etc.)
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Optimize performance, latency, and cost of AI systems
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Evaluate model outputs and implement guardrails (safety, hallucination reduction)
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Collaborate with product and engineering teams to define AI features
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Deploy and monitor AI services in cloud environments (AWS, Azure, GCP)
Requirements
~1 min readStrong programming skills in Python (preferred) or similar languages
Experience working with LLMs and GenAI frameworks (LangChain, LlamaIndex, etc.)
Solid understanding of RAG architectures and embeddings
Experience building APIs and scalable backend systems
Familiarity with prompt engineering and evaluation techniques
Understanding of vector search and semantic retrieval
Experience with cloud platforms and containerization (Docker, Kubernetes is a plus)
Experience with fine-tuning or adapting LLMs
Knowledge of transformers and NLP fundamentals
Experience with agent-based systems or tool-using LLMs
Familiarity with ML Ops / LLM Ops practices
Experience with real-time conversational systems
Exposure to evaluation frameworks (RAG eval, LLM benchmarking)
Nice to Have
~1 min readExperience with multi-modal models (text, image, audio)
Knowledge of knowledge graphs or hybrid retrieval systems
At Accenture, we prioritize your health and well-being through comprehensive health insurance coverage and inclusive work arrangements. We value your growth and offer diverse learning and development paths, along with performance-based rewards. You'll also have access to resources for mental health and physical wellness, ensuring inclusivity and support. We provide additional financial support, flexible benefits, and care for your loved ones, respecting diverse circumstances.
The position is available exclusively for collaboration under an individual working contract (CIM).
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Visit us at www.accenture.com
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Location & Eligibility
Listing Details
- First seen
- May 21, 2026
- Last seen
- July 3, 2026
Posting Health
- Days active
- 47
- Repost count
- 0
- Trust Level
- 13%
- Scored at
- July 7, 2026
Signal breakdown
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